(1) Field of Invention
The present invention relates to a system for object and behavior recognition and, more particularly, to a multi-modular system which integrates modules for object detection, scene matching, and behavior recognition.
(2) Description of Related Art
Visual behavior recognition systems have numerous applications, such as automatic visual surveillance, human-computer interaction, and video indexing/retrieval. Several visual behavior recognition systems exist that rely solely on Bayesian networks, such as that described by Park et al. in “A Hierarchical Bayesian Network for Event Recognition of Human Actions and Interactions,” at the ACM SIGMM International Workshop on Video Surveillance, Berkeley, Calif., 2003. Alternatively, Hu et al. described visual behavior recognition systems which rely on neural networks alone, in “Learning Activity Patterns Using Fuzzy Self-Organizing Neural Network” in IEEE Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics, 2004. The systems described by Park et al. and Hu et al. are limited by initial domain knowledge and the inability to easily incorporate domain knowledge, respectively. In addition, features such as video forensics, data mining, and intelligent video archiving may not be explicitly included in the aforementioned behavior recognition systems.
Prior art in the visual behavior recognition field does not consider system integration. Instead, the prior art focuses on object detection alone, scene matching alone, or behavior recognition alone. Such modules were described by Lowe in “Object Recognition from Local Scale-Invariant Features,” as presented at the International Conference on Computer Vision, Corfu, Greece, 1999, and Lazelbnik et al. in “Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories” as presented at the IEEE Conference on Computer Vision and Pattern Recognition, New York, N.Y. Similar modules were also described by Park et al. and Hu et al., as referenced above.
Because the prior art does not consider system integration, the prior art is limited in its inability to automatically recognize, learn, and adapt to simple and complex visual behaviors. Thus, a continuing need exists for a system which integrates object and behavior recognition and is not limited by initial domain knowledge.